Main Tab 1

Column

Column Tab 1

# A tibble: 297 × 14
     age   sex    cp trestbps  chol   fbs restecg thalach exang oldpeak  slop
   <dbl> <dbl> <dbl>    <dbl> <dbl> <dbl>   <dbl>   <dbl> <dbl>   <dbl> <dbl>
 1    37     1     3      130   250     0       0     187     0     3.5     3
 2    41     0     2      130   204     0       2     172     0     1.4     1
 3    56     1     2      120   236     0       0     178     0     0.8     1
 4    57     0     4      120   354     0       0     163     1     0.6     1
 5    56     0     2      140   294     0       2     153     0     1.3     2
 6    57     1     3      150   168     0       0     174     0     1.6     1
 7    54     1     4      140   239     0       0     160     0     1.2     1
 8    48     0     3      130   275     0       0     139     0     0.2     1
 9    49     1     2      130   266     0       0     171     0     0.6     1
10    64     1     1      110   211     0       2     144     1     1.8     2
# … with 287 more rows, and 3 more variables: ca <dbl>, thal <dbl>,
#   `pred-2class` <dbl>

Column Tab 2

age sex cp trestbps chol fbs restecg thalach exang oldpeak slop ca thal pred-2class
37 1 3 130 250 0 0 187 0 3.5 3 0 3 0
41 0 2 130 204 0 2 172 0 1.4 1 0 3 0
56 1 2 120 236 0 0 178 0 0.8 1 0 3 0
57 0 4 120 354 0 0 163 1 0.6 1 0 3 0
56 0 2 140 294 0 2 153 0 1.3 2 0 3 0
57 1 3 150 168 0 0 174 0 1.6 1 0 3 0
54 1 4 140 239 0 0 160 0 1.2 1 0 3 0
48 0 3 130 275 0 0 139 0 0.2 1 0 3 0
49 1 2 130 266 0 0 171 0 0.6 1 0 3 0
64 1 1 110 211 0 2 144 1 1.8 2 0 3 0
58 0 1 150 283 1 2 162 0 1.0 1 0 3 0
58 1 2 120 284 0 2 160 0 1.8 2 0 3 1
50 0 3 120 219 0 0 158 0 1.6 2 0 3 0
58 0 3 120 340 0 0 172 0 0.0 1 0 3 0
66 0 1 150 226 0 0 114 0 2.6 3 0 3 0
43 1 4 150 247 0 0 171 0 1.5 1 0 3 0
64 1 3 140 335 0 0 158 0 0.0 1 0 3 1
44 1 3 130 233 0 0 179 1 0.4 1 0 3 0
42 1 4 140 226 0 0 178 0 0.0 1 0 3 0
61 1 3 150 243 1 0 137 1 1.0 2 0 3 0
59 1 3 150 212 1 0 157 0 1.6 1 0 3 0
61 0 4 130 330 0 2 169 0 0.0 1 0 3 1
51 1 3 110 175 0 0 123 0 0.6 1 0 3 0
53 1 3 130 197 1 2 152 0 1.2 3 0 3 0
44 1 2 130 219 0 2 188 0 0.0 1 0 3 0
46 0 3 142 177 0 2 160 1 1.4 3 0 3 0
54 0 3 135 304 1 0 170 0 0.0 1 0 3 0
60 1 3 140 185 0 2 155 0 3.0 2 0 3 1
46 1 3 150 231 0 0 147 0 3.6 2 0 3 1
65 0 3 155 269 0 0 148 0 0.8 1 0 3 0
65 0 3 160 360 0 2 151 0 0.8 1 0 3 0
48 1 2 130 245 0 2 180 0 0.2 2 0 3 0
45 1 4 104 208 0 2 148 1 3.0 2 0 3 0
53 0 4 130 264 0 2 143 0 0.4 2 0 3 0
39 1 3 140 321 0 2 182 0 0.0 1 0 3 0
52 1 2 120 325 0 0 172 0 0.2 1 0 3 0
44 1 3 140 235 0 2 180 0 0.0 1 0 3 0
47 1 3 138 257 0 2 156 0 0.0 1 0 3 0
53 0 4 138 234 0 2 160 0 0.0 1 0 3 0
51 0 3 130 256 0 2 149 0 0.5 1 0 3 0
66 1 4 120 302 0 2 151 0 0.4 2 0 3 0
44 0 3 108 141 0 0 175 0 0.6 2 0 3 0
63 0 3 135 252 0 2 172 0 0.0 1 0 3 0
48 1 4 122 222 0 2 186 0 0.0 1 0 3 0
45 1 4 115 260 0 2 185 0 0.0 1 0 3 0
34 1 1 118 182 0 2 174 0 0.0 1 0 3 0
58 1 3 140 211 1 2 165 0 0.0 1 0 3 0
35 0 4 138 183 0 0 182 0 1.4 1 0 3 0
51 1 3 100 222 0 0 143 1 1.2 2 0 3 0
45 0 2 130 234 0 2 175 0 0.6 2 0 3 0
44 1 2 120 220 0 0 170 0 0.0 1 0 3 0
62 0 4 124 209 0 0 163 0 0.0 1 0 3 0
29 1 2 130 204 0 2 202 0 0.0 1 0 3 0
51 1 4 140 261 0 2 186 1 0.0 1 0 3 0
43 0 3 122 213 0 0 165 0 0.2 2 0 3 0
55 0 2 135 250 0 2 161 0 1.4 2 0 3 0
51 1 3 125 245 1 2 166 0 2.4 2 0 3 0
59 1 2 140 221 0 0 164 1 0.0 1 0 3 0
52 1 2 128 205 1 0 184 0 0.0 1 0 3 0
47 1 3 108 243 0 0 152 0 0.0 1 0 3 1
41 1 3 112 250 0 0 179 0 0.0 1 0 3 0
45 1 2 128 308 0 2 170 0 0.0 1 0 3 0
42 0 4 102 265 0 2 122 0 0.6 2 0 3 0
54 0 3 110 214 0 0 158 0 1.6 2 0 3 0
58 0 4 100 248 0 2 122 0 1.0 2 0 3 0
45 0 2 112 160 0 0 138 0 0.0 2 0 3 0
59 0 4 174 249 0 0 143 1 0.0 2 0 3 1
62 0 4 140 394 0 2 157 0 1.2 2 0 3 0
60 0 4 158 305 0 2 161 0 0.0 1 0 3 1
50 1 3 129 196 0 0 163 0 0.0 1 0 3 0
68 0 3 120 211 0 2 115 0 1.5 2 0 3 0
45 0 4 138 236 0 2 152 1 0.2 2 0 3 0
50 0 2 120 244 0 0 162 0 1.1 1 0 3 0
59 1 1 160 273 0 2 125 0 0.0 1 0 3 1
50 0 4 110 254 0 2 159 0 0.0 1 0 3 0
64 0 4 180 325 0 0 154 1 0.0 1 0 3 0
55 1 2 130 262 0 0 155 0 0.0 1 0 3 0
62 0 4 150 244 0 0 154 1 1.4 2 0 3 1
37 0 3 120 215 0 0 170 0 0.0 1 0 3 0
41 1 3 130 214 0 2 168 0 2.0 2 0 3 0
46 0 2 105 204 0 0 172 0 0.0 1 0 3 0
46 0 4 138 243 0 2 152 1 0.0 2 0 3 0
59 1 4 138 271 0 2 182 0 0.0 1 0 3 0
41 0 3 112 268 0 2 172 1 0.0 1 0 3 0
54 0 3 108 267 0 2 167 0 0.0 1 0 3 0
39 0 3 94 199 0 0 179 0 0.0 1 0 3 0
34 0 2 118 210 0 0 192 0 0.7 1 0 3 0
47 1 4 112 204 0 0 143 0 0.1 1 0 3 0
52 0 3 136 196 0 2 169 0 0.1 2 0 3 0
55 0 4 180 327 0 1 117 1 3.4 2 0 3 1
49 0 2 134 271 0 0 162 0 0.0 2 0 3 0
42 1 2 120 295 0 0 162 0 0.0 1 0 3 0
41 1 2 110 235 0 0 153 0 0.0 1 0 3 0
41 0 2 126 306 0 0 163 0 0.0 1 0 3 0
49 0 4 130 269 0 0 163 0 0.0 1 0 3 0
60 0 3 120 178 1 0 96 0 0.0 1 0 3 0
67 1 4 120 237 0 0 71 0 1.0 2 0 3 1
62 1 2 128 208 1 2 140 0 0.0 1 0 3 0
51 0 3 120 295 0 2 157 0 0.6 1 0 3 0
43 1 4 115 303 0 0 181 0 1.2 2 0 3 0
42 0 3 120 209 0 0 173 0 0.0 2 0 3 0
76 0 3 140 197 0 1 116 0 1.1 2 0 3 0
70 1 2 156 245 0 2 143 0 0.0 1 0 3 0
60 0 1 150 240 0 0 171 0 0.9 1 0 3 0
44 1 3 120 226 0 0 169 0 0.0 1 0 3 0
42 1 3 130 180 0 0 150 0 0.0 1 0 3 0
71 0 4 112 149 0 0 125 0 1.6 2 0 3 0
39 0 3 138 220 0 0 152 0 0.0 2 0 3 0
58 0 4 130 197 0 0 131 0 0.6 2 0 3 0
47 1 3 130 253 0 0 179 0 0.0 1 0 3 0
35 1 2 122 192 0 0 174 0 0.0 1 0 3 0
56 1 2 120 240 0 0 169 0 0.0 3 0 3 0
55 0 2 132 342 0 0 166 0 1.2 1 0 3 0
63 0 4 124 197 0 0 136 1 0.0 2 0 3 1
41 1 2 120 157 0 0 182 0 0.0 1 0 3 0
65 0 3 140 417 1 2 157 0 0.8 1 1 3 0
41 0 2 105 198 0 0 168 0 0.0 1 1 3 0
44 1 4 112 290 0 2 153 0 0.0 1 1 3 1
54 1 3 125 273 0 2 152 0 0.5 3 1 3 0
51 1 1 125 213 0 2 125 1 1.4 1 1 3 0
44 1 4 110 197 0 2 177 0 0.0 1 1 3 1
51 0 3 140 308 0 2 142 0 1.5 1 1 3 0
52 1 2 134 201 0 0 158 0 0.8 1 1 3 0
57 0 4 128 303 0 2 159 0 0.0 1 1 3 0
71 0 3 110 265 1 2 130 0 0.0 1 1 3 0
56 1 4 125 249 1 2 144 1 1.2 2 1 3 1
65 1 1 138 282 1 2 174 0 1.4 2 1 3 1
60 0 3 102 318 0 0 160 0 0.0 1 1 3 0
64 1 4 120 246 0 2 96 1 2.2 3 1 3 1
54 0 2 132 288 1 2 159 1 0.0 1 1 3 0
43 1 3 130 315 0 0 162 0 1.9 1 1 3 0
69 1 1 160 234 1 2 131 0 0.1 2 1 3 0
52 1 4 112 230 0 0 160 0 0.0 1 1 3 1
67 0 3 152 277 0 0 172 0 0.0 1 1 3 0
54 1 4 110 206 0 2 108 1 0.0 2 1 3 1
66 1 4 112 212 0 2 132 1 0.1 1 1 3 1
74 0 2 120 269 0 2 121 1 0.2 1 1 3 0
54 0 3 160 201 0 0 163 0 0.0 1 1 3 0
47 1 4 110 275 0 2 118 1 1.0 2 1 3 1
44 0 3 118 242 0 0 149 0 0.3 2 1 3 0
61 1 4 138 166 0 2 125 1 3.6 2 1 3 1
66 0 3 146 278 0 2 152 0 0.0 2 1 3 0
57 1 2 154 232 0 2 164 0 0.0 1 1 3 1
57 0 2 130 236 0 2 174 0 0.0 2 1 3 1
62 0 4 140 268 0 2 160 0 3.6 3 2 3 1
69 0 1 140 239 0 0 151 0 1.8 1 2 3 0
71 0 2 160 302 0 0 162 0 0.4 1 2 3 0
48 1 3 124 255 1 0 175 0 0.0 1 2 3 0
42 1 1 148 244 0 2 178 0 0.8 1 2 3 0
63 0 2 140 195 0 0 179 0 0.0 1 2 3 0
67 1 4 100 299 0 2 125 1 0.9 2 2 3 1
64 0 4 130 303 0 0 122 0 2.0 2 2 3 0
63 0 4 108 269 0 0 169 1 1.8 2 2 3 1
54 1 4 122 286 0 2 116 1 3.2 2 2 3 1
61 1 1 134 234 0 0 145 0 2.6 2 2 3 1
67 0 4 106 223 0 0 142 0 0.3 1 2 3 0
58 0 2 136 319 1 2 152 0 0.0 1 2 3 1
59 1 1 134 204 0 0 162 0 0.8 1 2 3 1
67 1 4 160 286 0 2 108 1 1.5 2 3 3 1
70 1 4 130 322 0 2 109 0 2.4 2 3 3 1
77 1 4 125 304 0 2 162 1 0.0 1 3 3 1
53 1 3 130 246 1 2 173 0 0.0 1 3 3 0
62 0 4 138 294 1 0 106 0 1.9 2 3 3 1
49 1 3 118 149 0 2 126 0 0.8 1 3 3 1
63 1 1 145 233 1 2 150 0 2.3 3 0 6 0
57 1 4 140 192 0 0 148 0 0.4 2 0 6 0
52 1 1 118 186 0 2 190 0 0.0 2 0 6 0
41 1 2 135 203 0 0 132 0 0.0 2 0 6 0
57 1 4 110 201 0 0 126 1 1.5 2 0 6 0
42 1 4 136 315 0 0 125 1 1.8 2 0 6 1
66 1 4 160 228 0 2 138 0 2.3 1 0 6 0
44 1 4 120 169 0 0 144 1 2.8 3 0 6 1
56 1 3 130 256 1 2 142 1 0.6 2 1 6 1
57 1 4 150 276 0 2 112 1 0.6 2 1 6 1
56 1 4 132 184 0 2 105 1 2.1 2 1 6 1
59 1 3 126 218 1 0 134 0 2.2 2 1 6 1
65 1 4 110 248 0 2 158 0 0.6 1 2 6 1
64 1 4 145 212 0 2 132 0 2.0 2 2 6 1
58 0 4 170 225 1 2 146 1 2.8 2 2 6 1
59 1 4 164 176 1 2 90 0 1.0 2 2 6 1
66 1 2 160 246 0 0 120 1 0.0 2 3 6 1
58 1 4 114 318 0 1 140 0 4.4 3 3 6 1
53 1 4 140 203 1 2 155 1 3.1 3 0 7 1
44 1 2 120 263 0 0 173 0 0.0 1 0 7 0
52 1 3 172 199 1 0 162 0 0.5 1 0 7 0
48 1 2 110 229 0 0 168 0 1.0 3 0 7 1
40 1 4 110 167 0 2 114 1 2.0 2 0 7 1
59 1 4 135 234 0 0 161 0 0.5 2 0 7 0
43 1 4 120 177 0 2 120 1 2.5 2 0 7 1
40 1 1 140 199 0 0 178 1 1.4 1 0 7 0
50 1 4 150 243 0 2 128 0 2.6 2 0 7 1
65 1 4 120 177 0 0 140 0 0.4 1 0 7 0
41 1 4 110 172 0 2 158 0 0.0 1 0 7 1
51 0 4 130 305 0 0 142 1 1.2 2 0 7 1
54 1 3 150 232 0 2 165 0 1.6 1 0 7 0
59 1 4 170 326 0 2 140 1 3.4 3 0 7 1
58 1 4 150 270 0 2 111 1 0.8 1 0 7 1
68 1 3 180 274 1 2 150 1 1.6 2 0 7 1
54 1 2 108 309 0 0 156 0 0.0 1 0 7 0
39 1 4 118 219 0 0 140 0 1.2 2 0 7 1
61 0 4 145 307 0 2 146 1 1.0 2 0 7 1
43 0 4 132 341 1 2 136 1 3.0 2 0 7 1
55 1 4 140 217 0 0 111 1 5.6 3 0 7 1
54 1 3 120 258 0 2 147 0 0.4 2 0 7 0
70 1 4 145 174 0 0 125 1 2.6 3 0 7 1
35 1 4 120 198 0 0 130 1 1.6 2 0 7 1
59 1 1 170 288 0 2 159 0 0.2 2 0 7 1
64 1 3 125 309 0 0 131 1 1.8 2 0 7 1
58 1 3 105 240 0 2 154 1 0.6 2 0 7 0
52 1 1 152 298 1 0 178 0 1.2 2 0 7 0
67 0 3 115 564 0 2 160 0 1.6 2 0 7 0
51 1 4 140 299 0 0 173 1 1.6 1 0 7 1
46 1 2 101 197 1 0 156 0 0.0 1 0 7 0
57 1 4 132 207 0 0 168 1 0.0 1 0 7 0
35 1 4 126 282 0 2 156 1 0.0 1 0 7 1
53 1 4 142 226 0 2 111 1 0.0 1 0 7 0
48 1 4 124 274 0 2 166 0 0.5 2 0 7 1
59 1 1 178 270 0 2 145 0 4.2 3 0 7 0
42 1 3 120 240 1 0 194 0 0.8 3 0 7 0
64 0 3 140 313 0 0 133 0 0.2 1 0 7 0
43 1 4 110 211 0 0 161 0 0.0 1 0 7 0
50 1 4 144 200 0 2 126 1 0.9 2 0 7 1
38 1 1 120 231 0 0 182 1 3.8 2 0 7 1
56 1 1 120 193 0 2 162 0 1.9 2 0 7 0
56 1 4 130 283 1 2 103 1 1.6 3 0 7 1
46 1 4 120 249 0 2 144 0 0.8 1 0 7 1
57 1 2 124 261 0 0 141 0 0.3 1 0 7 1
40 1 4 152 223 0 0 181 0 0.0 1 0 7 1
64 1 1 170 227 0 2 155 0 0.6 2 0 7 0
56 1 2 130 221 0 2 163 0 0.0 1 0 7 0
67 1 3 152 212 0 2 150 0 0.8 2 0 7 1
57 0 4 140 241 0 0 123 1 0.2 2 0 7 1
45 1 1 110 264 0 0 132 0 1.2 2 0 7 1
63 1 4 130 254 0 2 147 0 1.4 2 1 7 1
55 1 4 132 353 0 0 132 1 1.2 2 1 7 1
58 1 3 112 230 0 2 165 0 2.5 2 1 7 1
60 1 4 130 253 0 0 144 1 1.4 1 1 7 1
54 1 4 124 266 0 2 109 1 2.2 2 1 7 1
50 1 3 140 233 0 0 163 0 0.6 2 1 7 1
54 1 4 120 188 0 0 113 0 1.4 2 1 7 1
60 1 4 125 258 0 2 141 1 2.8 2 1 7 1
52 1 4 128 255 0 0 161 1 0.0 1 1 7 1
59 1 4 110 239 0 2 142 1 1.2 2 1 7 1
59 1 4 140 177 0 0 162 1 0.0 1 1 7 1
57 1 3 128 229 0 2 150 0 0.4 2 1 7 1
61 1 4 120 260 0 0 140 1 3.6 2 1 7 1
62 0 3 130 263 0 0 97 0 1.2 2 1 7 1
65 1 4 135 254 0 2 127 0 2.8 2 1 7 1
54 1 4 110 239 0 0 126 1 2.8 2 1 7 1
51 1 3 94 227 0 0 154 1 0.0 1 1 7 0
62 1 2 120 281 0 2 103 0 1.4 2 1 7 1
55 1 4 160 289 0 2 145 1 0.8 2 1 7 1
68 1 3 118 277 0 0 151 0 1.0 1 1 7 0
70 1 3 160 269 0 0 112 1 2.9 2 1 7 1
57 1 4 152 274 0 0 88 1 1.2 2 1 7 1
54 1 2 192 283 0 2 195 0 0.0 1 1 7 1
57 1 3 150 126 1 0 173 0 0.2 1 1 7 0
58 1 4 100 234 0 0 156 0 0.1 1 1 7 1
58 1 4 146 218 0 0 105 0 2.0 2 1 7 1
64 1 4 128 263 0 0 105 1 0.2 2 1 7 0
61 1 4 140 207 0 2 138 1 1.9 1 1 7 1
57 1 4 110 335 0 0 143 1 3.0 2 1 7 1
55 0 4 128 205 0 1 130 1 2.0 2 1 7 1
61 1 4 148 203 0 0 161 0 0.0 1 1 7 1
57 1 4 130 131 0 0 115 1 1.2 2 1 7 1
67 1 4 120 229 0 2 129 1 2.6 2 2 7 1
58 1 3 132 224 0 2 173 0 3.2 1 2 7 1
60 1 4 130 206 0 2 132 1 2.4 2 2 7 1
60 1 4 117 230 1 0 160 1 1.4 1 2 7 1
60 1 4 145 282 0 2 142 1 2.8 2 2 7 1
67 1 4 125 254 1 0 163 0 0.2 2 2 7 1
62 1 4 120 267 0 0 99 1 1.8 2 2 7 1
60 0 4 150 258 0 2 157 0 2.6 2 2 7 1
48 1 4 130 256 1 2 150 1 0.0 1 2 7 1
56 0 4 200 288 1 2 133 1 4.0 3 2 7 1
58 1 4 125 300 0 2 171 0 0.0 1 2 7 1
60 1 4 140 293 0 2 170 0 1.2 2 2 7 1
56 0 4 134 409 0 2 150 1 1.9 2 2 7 1
58 1 4 128 259 0 2 130 1 3.0 2 2 7 1
66 0 4 178 228 1 0 165 1 1.0 2 2 7 1
53 1 4 123 282 0 0 95 1 2.0 2 2 7 1
52 1 4 125 212 0 0 168 0 1.0 1 2 7 1
46 1 4 140 311 0 0 120 1 1.8 2 2 7 1
63 1 4 140 187 0 2 144 1 4.0 1 2 7 1
68 1 4 144 193 1 0 141 0 3.4 2 2 7 1
65 0 4 150 225 0 2 114 0 1.0 2 3 7 1
58 1 4 128 216 0 2 131 1 2.2 2 3 7 1
62 0 4 160 164 0 2 145 0 6.2 3 3 7 1
62 1 3 130 231 0 0 146 0 1.8 2 3 7 0
49 1 3 120 188 0 0 139 0 2.0 2 3 7 1
63 1 4 130 330 1 2 132 1 1.8 1 3 7 1
63 0 4 150 407 0 2 154 0 4.0 2 3 7 1
57 1 4 165 289 1 2 124 0 1.0 2 3 7 1
52 1 4 108 233 1 0 147 0 0.1 1 3 7 0
69 1 3 140 254 0 2 146 0 2.0 2 3 7 1
51 1 4 140 298 0 0 122 1 4.2 2 3 7 1
45 1 4 142 309 0 2 147 1 0.0 2 3 7 1

Column Tab 3

Column

Row 1

Row 2

Main Tab 2

Column

1. Plotly for R

Plotly is an R package for creating interactive web-based graphs via plotly’s JavaScript graphing library, plotly.js.

The plotly R package serializes ggplot2 figures into Plotly’s universal graph JSON. plotly::ggplotly will crawl the ggplot2 figure, extract and translate all of the attributes of the ggplot2 figure into JSON (the colors, the axes, the chart type, etc), and draw the graph with plotly.js. Furthermore, you have the option of manipulating the Plotly object with the style function.

2. Cutomizing the Layout

Since the ggplotly() function returns a plotly object, we can manipulate that object in the same way that we would manipulate any other plotly object. A simple and useful application of this is to specify interaction modes, like plotly.js’ layout.dragmode for specifying the mode of click+drag events.

3. Example

library(plotly)
df <- data.frame(x=c(1, 2, 3, 4), y=c(1, 5, 3, 5), group=c('A', 'A', 'B', 'B'))
p <- ggplot(data=df, aes(x=x, y=y, colour=group)) + geom_point()
ggplotly(p)

Column

Row 1

Row 2


---
title: "Heart Disease"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    logo: logo.png
    source_code: embed
    social: menu
---

```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse)
library(plotly)
library(knitr)
library(DT)

df <- read_csv('Heart_Disease.csv')

# Create a ggplot object
p <- df %>% 
  mutate(Disease = factor(`pred-2class`)) %>% 
  ggplot()+ 
  geom_bar(mapping=aes(x=sex, fill=Disease), 
           position = 'fill')+
  labs(y='Proportion', fill='Heart Disease')

p1 <- df %>% 
  mutate(Disease = factor(`pred-2class`)) %>% 
  ggplot()+ 
  geom_density(mapping=aes(x=age, color=Disease))+
  facet_wrap(~thal)
```

{.sidebar}
=======================================================================

### 1. Heart Disease

Heart disease is one of the most prevalent causes of death around the world. There are many factors that are involved in whether someone is likely to have heart disease or not.

### 2. Flexdashboard and Plotly

This interactive uses `flexdashboard` and `plotly` to visualize the data. 

Main Tab 1
=======================================================================

Column {data-width=500, .tabset}
-----------------------------------------------------------------------

### Column Tab 1

```{r}
df
```


### Column Tab 2

```{r}
kable(df)
```


### Column Tab 3

```{r}
datatable(df, options = list(
  pageLength = 25
))
```


Column {data-width=500}
-----------------------------------------------------------------------

### Row 1

```{r}
p
```

### Row 2

```{r}
ggplotly(p)
```


Main Tab 2
=======================================================================

Column {data-width=500}
-----------------------------------------------------------------------

#### 1. Plotly for R

Plotly is an R package for creating interactive web-based graphs via plotly's JavaScript graphing library, plotly.js.

The plotly R package serializes ggplot2 figures into Plotly's universal graph JSON. plotly::ggplotly will crawl the ggplot2 figure, extract and translate all of the attributes of the ggplot2 figure into JSON (the colors, the axes, the chart type, etc), and draw the graph with plotly.js. Furthermore, you have the option of manipulating the Plotly object with the style function.


#### 2. Cutomizing the Layout

Since the ggplotly() function returns a plotly object, we can manipulate that object in the same way that we would manipulate any other plotly object. A simple and useful application of this is to specify interaction modes, like plotly.js' layout.dragmode for specifying the mode of click+drag events.


#### 3. Example

```{r, echo=TRUE, eval=TRUE}
library(plotly)
df <- data.frame(x=c(1, 2, 3, 4), y=c(1, 5, 3, 5), group=c('A', 'A', 'B', 'B'))
p <- ggplot(data=df, aes(x=x, y=y, colour=group)) + geom_point()
ggplotly(p)
```



Column {data-width=500}
-----------------------------------------------------------------------

### Row 1

```{r}
p1
```

### Row 2

```{r}
ggplotly(p1)
```